Research Fellow / Senior Research Assistant in Statistical Data Analysis

Singapore University of Technology and Design


Research Fellow/Senior Research Assistant

Job no: 494444

Work type: Contract, full-time

Location: Singapore

Categories: Masters, PhD, Others, Math/Statistics, IT - Network/Systems/Database, IT - Software, Others

Project Overview

This research program focuses on creating a cross-disciplinary platform through public-private collaboration (HDB-SUTD-MIT-EDF) to rethink the future of housing in Singapore. Through a deeper understanding of the changing demographics and neighbourhood-based Quality of Life assessment, the program aims to develop various conceptual frameworks and practical tools to promote vibrant collaborative urban communities, which will then enable future town planning and housing design towards the development of a New Urban Kampung. 

Working alongside a multidisciplinary team of social scientists, engineers, designers, and data scientists, this programme covers four areas of study:

  1. Redefine geo-sociographic segments of HDB residents

  2. Develop neighbourhood-based Quality of Life framework and indicators for HDB towns

  3. Understand residents’ socio-spatial behaviours in community development

  4. Urban analytics for modelling, simulation, and prediction

Job Description

This full-time researcher position will focus on supporting the first and third part of the programme with statistical data analysis. Applicants are expected to have the following desired skills:

  • Well-versed in R and R libraries, including but not limited to tidyverse, psych, spatial libraries, etc.

  • Skilled in spatial statistics and analysis (e.g. spatial autocorrelation, spatial regression modelling, etc.) 

  • Knowledge in statistical tests for multivariable responses

  • Experienced in dimension reduction strategies (e.g. PCA), segmentation analysis, cluster analysis, multiple regression models (e.g. linear regressions, logistic regressions, random forest, etc.)

  • Familiarity with Elasticsearch, Bash, Git, and Bookdown

Domain Background (one of)

  • Urban Science, Computer Science, Data Science, Social Science, Statistics or equivalent


  • Relevant master’s degree or doctorate in one of the above fields

To apply

Interested applicants are invited to send in their documents to

  • Cover letter

  • C.V.

  • Links to current online work / GitHub (if relevant) or recent publication

We regret that only shortlisted candidates will be notified. The position can start from September 2020 or later.

Applications close: 03 Oct 2020 Singapore Standard Time

In your application, please refer to